{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction to atomman: Gamma surface plotting\n",
    "\n",
    "__Lucas M. Hale__, [lucas.hale@nist.gov](mailto:lucas.hale@nist.gov?Subject=ipr-demo), _Materials Science and Engineering Division, NIST_.\n",
    "    \n",
    "[Disclaimers](http://www.nist.gov/public_affairs/disclaimer.cfm) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Introduction<a id='section1'></a>\n",
    "\n",
    "This Notebook outlines the GammaSurface class and the various stacking fault plots that it can generate.  See the [4.3. Stacking fault generator Notebook](4.3._Stacking_fault_generator.html) for generating systems containing stacking faults."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Library Imports**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "atomman version = 1.4.0\n",
      "Notebook executed on 2021-08-05\n"
     ]
    }
   ],
   "source": [
    "# Standard Python libraries\n",
    "from pathlib import Path\n",
    "import datetime\n",
    "\n",
    "# http://www.numpy.org/\n",
    "import numpy as np\n",
    "\n",
    "# https://github.com/usnistgov/atomman\n",
    "import atomman as am\n",
    "import atomman.unitconvert as uc\n",
    "\n",
    "# https://matplotlib.org/\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "# Show atomman version\n",
    "print('atomman version =', am.__version__)\n",
    "\n",
    "# Show date of Notebook execution\n",
    "print('Notebook executed on', datetime.date.today())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Underlying theory<a id='section2'></a>\n",
    "\n",
    "Generalized stacking fault energy maps ($\\gamma$-surfaces) provide 2D maps of the stacking fault energy associated with arbitrary shifts along a crystallographic fault plane. Typically, the fault plane corresponds to one of the crystal's slip planes and the stacking fault energies and pathways influence dislocation structures and dislocation slip.\n",
    "\n",
    "A $\\gamma$-surface is defined by the crystal and the fault plane. Starting in an unfaulted configuration, the atoms on one side of the fault plane are shifted by a vector $\\mathbf{d}$ which is within the fault plane.  The generalized stacking fault energy for a given shift, $\\gamma_{gsf}(\\mathbf{d})$, is computed as the difference in potential energy, $U$ of the shifted configuration relative to the corresponding unshifted configuration ($\\mathbf{d}=\\mathbf{0}$) divided by the fault plane area, $A_{fault}$\n",
    "\n",
    "$$\\gamma_{gsf}(\\mathbf{d}) = \\frac{U(\\mathbf{d}) - U(\\mathbf{0})}{A_{fault}}$$\n",
    "\n",
    "The measured $\\gamma_{gsf}$ values may be \"unrelaxed\", in which case no atomic relaxations are allowed, or \"relaxed\", in which atoms are allowed to move only in the direction normal to the slip plane to lower the system's energy.  For relaxed $\\gamma$-surfaces, the relaxation distance, $\\delta_{\\bot}$, can be evaluated using the centers of mass of the atoms on the two sides of the fault plane, $\\mathbf{R}^+$ and $\\mathbf{R}^-$, and measuring how the plane normal component $\\bot$ changes relative to the unshifted state\n",
    "\n",
    "$$ \\mathbf{R} = \\frac{\\sum_{i=1}^{n}m_i\\mathbf{r_i}}{\\sum_{i=1}^{n}m_i} $$\n",
    "\n",
    "$$ \\delta_{\\bot} = \\left(R_{\\bot}^+(\\mathbf{d}) - R_{\\bot}^-(\\mathbf{d})\\right) - \\left(R_{\\bot}^+(\\mathbf{0}) - R_{\\bot}^-(\\mathbf{0})\\right)$$\n",
    "\n",
    "As a $\\gamma$-surface is a 2D map, the applied shift, $\\mathbf{d}$, can be expressed using two non-parallel vectors within the fault plane, $\\mathbf{a_1}$ and $\\mathbf{a_2}$. Taking $\\mathbf{a_1}$ and $\\mathbf{a_2}$ as lattice vectors (i.e. vectors between two symetrically identical lattice sites) will define a 2D cell encompassing all possible unique stacking fault shifts for the fault plane.  $\\mathbf{d}$ can then be represented using fractional coordinates, $a_1$ and $a_2$, relative to $\\mathbf{a_1}$ and $\\mathbf{a_2}$\n",
    "\n",
    "$$ \\mathbf{d} = a_1 \\mathbf{a_1} + a_2 \\mathbf{a_2} $$\n",
    "\n",
    "The $\\gamma_{gsf}$ (and $\\delta_{\\bot}$) data is fit to interpolation models to provide continuous values between the measured points. Two interpolation models are fit to the data\n",
    "\n",
    "- A multiquadric radial basis function interpolation.\n",
    "- A nearest-value interpolation. \n",
    "\n",
    "To perform the fits, the data is replicated across the periodic bounds by shifting the $a_1$ and $a_2$ values by $\\pm 1$. The unique $a_1$ and $a_2$ values less than and closest to 0 and greater than and closest to 1 are identified, and all measured points between these two limits are fed into the fitting models to ensure smooth representation across the bounds.  Any arbitrary shift values $\\mathbf{d}$ are converted into $a_1$ and $a_2$ values between 0 and 1 for use in retrieving values from the fitted models."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Defining gamma surface data<a id='section3'></a>\n",
    "\n",
    "The atomman.defect.GammaSurface class offers interpolation and plotting options for generalized stacking fault data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1. Setting values\n",
    "\n",
    "The stacking fault data can be set directly either during class initialization or by using the GammaSurface.set() method.\n",
    "\n",
    "Parameters: \n",
    "\n",
    "- **a1vect** (*array-like object of length 3*) The a1 shifting vector.  If box is given, a1vect is taken as a crystal lattice vector, otherwise as a Cartesian vector.\n",
    "- **a2vect** (*array-like object of length 3*) The a2 shifting vector.  If box is given, a1vect is taken as a crystal lattice vector, otherwise as a Cartesian vector.\n",
    "- **a1** (*array-like object of length N*) List of fractional coordinates along a1vect corresponding to the E_gsf (and delta) values.\n",
    "- **a2** (*array-like object of length N*) List of fractional coordinates along a2vect corresponding to the E_gsf (and delta) values.\n",
    "- **E_gsf** (*array-like object of length N*) List of generalized stacking fault energies for the positions associated with the corresponding (a1, a2) fractional coordinates.\n",
    "- **box** (*atomman.Box, optional*) Defines unit cell box dimensions for conversion between crystal lattice and Cartesian vectors.   If not given, will be set as a square unit box, thus no conversion will occur (i.e. a1vect, a2vect will be Cartesian).\n",
    "- **delta** (*array-like object of length N, optional*) List of change in displacements normal to the fault plane for the positions associated with the corresponding (a1, a2) fractional coordinates."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Parameters for an Al fcc 111 stacking fault using 2008--Mendelev-M-I--Al--LAMMPS--ipr1\n",
    "box = am.Box.cubic(a=4.045259794316263)\n",
    "a1vect = np.array([ 0.0, -0.5, 0.5])\n",
    "a2vect = np.array([ 0.5, -0.5, 0.0])\n",
    "\n",
    "# Measured 30x30 grid of generalized stacking fault data\n",
    "a1 = np.array([0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667, 0.0, 0.03333333333333333, 0.06666666666666667, 0.1, 0.13333333333333333, 0.16666666666666666, 0.2, 0.23333333333333334, 0.26666666666666666, 0.3, 0.3333333333333333, 0.36666666666666664, 0.4, 0.43333333333333335, 0.4666666666666667, 0.5, 0.5333333333333333, 0.5666666666666667, 0.6, 0.6333333333333333, 0.6666666666666666, 0.7, 0.7333333333333333, 0.7666666666666666, 0.8, 0.8333333333333334, 0.8666666666666667, 0.9, 0.9333333333333333, 0.9666666666666667])\n",
    "a2 = np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.03333333333333333, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.06666666666666667, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.13333333333333333, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.23333333333333334, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.26666666666666666, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.3333333333333333, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.36666666666666664, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.4, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.43333333333333335, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.4666666666666667, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5333333333333333, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.5666666666666667, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6333333333333333, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.6666666666666666, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7333333333333333, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.7666666666666666, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8333333333333334, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.8666666666666667, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9333333333333333, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667, 0.9666666666666667])\n",
    "E_gsf = np.array([0.0, 0.0003276644660250489, 0.0013197032610667036, 0.0030080286990708206, 0.005299272889367739, 0.007853645516566367, 0.010344679818558007, 0.012746832373238334, 0.015027073432287454, 0.01713303089875586, 0.018964037324507355, 0.020359502522962633, 0.021289405537333824, 0.021852691822297415, 0.022145827289685307, 0.022235037181376597, 0.022145827289685307, 0.021852691822297415, 0.021289405537333824, 0.020359502522962633, 0.018964037324507355, 0.01713303089875586, 0.015027073432287454, 0.012746832373238334, 0.010344679818558007, 0.007853645516566367, 0.005299272889367739, 0.0030080286990708206, 0.0013197032610667036, 0.0003276644660250489, 0.0003276644660250489, 0.0009624286188679017, 0.0022516168853462543, 0.004179318519958506, 0.006502012537909789, 0.008836360637079085, 0.011071402674020946, 0.013163772621198347, 0.015069987998274524, 0.01676775797378991, 0.018202365560353467, 0.019266421370540104, 0.01992937325132262, 0.02028149454107946, 0.02042805135939521, 0.02042805137633013, 0.02028149454107946, 0.01992937325132262, 0.019266421370540104, 0.018202365560353467, 0.01676775797378991, 0.015069987998274524, 0.013163772621198347, 0.011071402674020946, 0.008836360637079085, 0.006502012537909789, 0.004179318519958506, 0.0022516168853462543, 0.0009624286188679017, 0.0003276644660250489, 0.0013197032610667036, 0.0022516168853462543, 0.00379342830708924, 0.005803543732471961, 0.00793645979564411, 0.010002224995159091, 0.011913305022139525, 0.013596628277462183, 0.015034223959459074, 0.016248082833591557, 0.017231759917201616, 0.017942818177434202, 0.01838247984870989, 0.018588416437931753, 0.018643586130194265, 0.018588416437931753, 0.01838247984870989, 0.017942818177434202, 0.017231759917201616, 0.016248082833591557, 0.015034223959459074, 0.013596628277462183, 0.011913305022139525, 0.010002224995159091, 0.00793645979564411, 0.005803543732471961, 0.00379342830708924, 0.0022516168853462543, 0.0013197032610667036, 0.001008906143675133, 0.0030080286990708206, 0.004179318519958506, 0.005803543732471961, 0.007637852288274728, 0.009496660797274951, 0.011243532636952849, 0.012743928196872886, 0.013936123292691541, 0.014847319113605083, 0.015549856853502065, 0.016082846740739055, 0.01645862282198508, 0.016705110082744275, 0.01682916112649225, 0.01682916112649225, 0.016705110082744275, 0.016458622823396964, 0.016082846740739055, 0.015549856853502065, 0.014847319113605083, 0.013936123292691541, 0.012743928195463569, 0.011243532636952849, 0.009496660797274951, 0.007637852288274728, 0.005803543732471961, 0.004179318519958506, 0.0030080286990708206, 0.0023998946753737717, 0.0023998946753737717, 0.005299272889367739, 0.006502012537909789, 0.00793645979564411, 0.009496660797274951, 0.011035628677366563, 0.01237392710762056, 0.013385589574354801, 0.01404488393495149, 0.014423942718867563, 0.014639725692955295, 0.014765683854799951, 0.014838711638586797, 0.014883062600264814, 0.01489480692722371, 0.014883062600264814, 0.014838711638586797, 0.014765683854799951, 0.014639725692955295, 0.014423942718867563, 0.01404488393495149, 0.013385589574354801, 0.01237392710762056, 0.011035628677366563, 0.009496660797274951, 0.00793645979564411, 0.006502012537909789, 0.005299272889367739, 0.004494424933099573, 0.004211052927859079, 0.004494424933099573, 0.007853645516566367, 0.008836360637079085, 0.010002224995159091, 0.011243532636952849, 0.01237392710762056, 0.013222604888781, 0.013701533360467543, 0.013831808215880651, 0.013724810143582959, 0.01351871945764962, 0.013288096454131046, 0.013053141110424394, 0.01288473799574951, 0.01288473799574951, 0.013053141110424394, 0.013288096454131046, 0.01351871945764962, 0.013724810143582959, 0.013831808215880651, 0.013701533360467543, 0.013222604888781, 0.01237392710762056, 0.011243532636952849, 0.010002224995159091, 0.008836360637079085, 0.007853645516566367, 0.007090113076005102, 0.006654577493741669, 0.006654577493741669, 0.007090113076005102, 0.010344679818558007, 0.011071402674020946, 0.011913305022139525, 0.012743928196872886, 0.013385589574354801, 0.013701533360467543, 0.013650790504842861, 0.013297636384243845, 0.012775745469630308, 0.01220434858125911, 0.011633781497279536, 0.011198475775133013, 0.011035966519916687, 0.011198475775133013, 0.011633781497279536, 0.01220434858125911, 0.012775745469630308, 0.013297636384243845, 0.013650790504842861, 0.013701533360467543, 0.013385589574354801, 0.012743928195463569, 0.011913305022139525, 0.011071402674020946, 0.010344679818558007, 0.009791920945171492, 0.009439135467834685, 0.009310068611476237, 0.009439135467834685, 0.009791920945171492, 0.012746832373238334, 0.013163772621198347, 0.013596628277462183, 0.013936123292691541, 0.01404488393495149, 0.013831808215880651, 0.013297636384243845, 0.012529422359386078, 0.011638354833823921, 0.01074148627431762, 0.010038128724558996, 0.009656642364574372, 0.009656642364574372, 0.010038128724558996, 0.01074148627431762, 0.011638354833823921, 0.012529422359386078, 0.013297636384243845, 0.013831808215880651, 0.01404488393495149, 0.013936123292691541, 0.013596628277462183, 0.013163772621198347, 0.012746832373238334, 0.012404093212327083, 0.012183307197516747, 0.012090801183497172, 0.012090801183497172, 0.012183307197516747, 0.012404093212327083, 0.015027073432287454, 0.015069987998274524, 0.015034223959459074, 0.014847319113605083, 0.014423942718867563, 0.013724810143582959, 0.012775745469630308, 0.011638354833823921, 0.010430230660255049, 0.009449322004070611, 0.008844617563989746, 0.00864189871015902, 0.008844617563989746, 0.009449322004070611, 0.010430230660255049, 0.011638354833823921, 0.012775745469630308, 0.013724810143582959, 0.014423942718867563, 0.014847319113605083, 0.015034223959459074, 0.015069987998274524, 0.015027073432287454, 0.014934876376596327, 0.01483061319175465, 0.014740550396192733, 0.014701162449128703, 0.014740550396192733, 0.01483061319175465, 0.014934876376596327, 0.01713303089875586, 0.01676775797378991, 0.016248082833591557, 0.015549856853502065, 0.014639725692955295, 0.01351871945764962, 0.01220434858125911, 0.01074148627431762, 0.009449322004070611, 0.008578811099234605, 0.00815484933711049, 0.00815484933711049, 0.008578811099234605, 0.009449322004070611, 0.01074148627431762, 0.01220434858125911, 0.01351871945764962, 0.014639725692955295, 0.015549856853502065, 0.016248082833591557, 0.01676775797378991, 0.01713303089875586, 0.01732800024220794, 0.017369215082978437, 0.017321437948693633, 0.017272284193973794, 0.017272284193973794, 0.017321437948693633, 0.017369215082978437, 0.01732800024220794, 0.018964037324507355, 0.018202365560353467, 0.017231759917201616, 0.016082846740739055, 0.014765683854799951, 0.013288096454131046, 0.011633781497279536, 0.010038128724558996, 0.008844617563989746, 0.00815484933711049, 0.007931982282131142, 0.00815484933711049, 0.008844617563989746, 0.010038128724558996, 0.011633781497279536, 0.013288096454131046, 0.014765683854799951, 0.016082846740739055, 0.017231759917201616, 0.018202365560353467, 0.018964037324507355, 0.019454139208464893, 0.019694360589358625, 0.01977827285566793, 0.01978984714716384, 0.019786649819980306, 0.01978984714716384, 0.01977827285566793, 0.019694360589358625, 0.019454139208464893, 0.020359502522962633, 0.019266421370540104, 0.017942818177434202, 0.01645862282198508, 0.014838711638586797, 0.013053141110424394, 0.011198475775133013, 0.009656642364574372, 0.00864189871015902, 0.00815484933711049, 0.00815484933711049, 0.00864189871015902, 0.009656642364574372, 0.011198475775133013, 0.013053141110424394, 0.014838711638586797, 0.016458622823396964, 0.017942818177434202, 0.019266421370540104, 0.020359502522962633, 0.021147064770108075, 0.021649358382385377, 0.021934945102187603, 0.022076143474118026, 0.022128736159221365, 0.022128736159221365, 0.022076143474118026, 0.021934945102187603, 0.021649358382385377, 0.021147064770108075, 0.021289405537333824, 0.01992937325132262, 0.01838247984870989, 0.016705110082744275, 0.014883062600264814, 0.01288473799574951, 0.011035966519916687, 0.009656642364574372, 0.008844617563989746, 0.008578811099234605, 0.008844617563989746, 0.009656642364574372, 0.011035966519916687, 0.01288473799574951, 0.014883062600264814, 0.016705110082744275, 0.01838247984870989, 0.01992937325132262, 0.021289405537333824, 0.022370099121114623, 0.0231503150713325, 0.02366759427728574, 0.023980226181548533, 0.024139292094786883, 0.02418571534118722, 0.024139292094786883, 0.023980226181548533, 0.02366759427728574, 0.0231503150713325, 0.022370099121114623, 0.021852691822297415, 0.02028149454107946, 0.018588416437931753, 0.01682916112649225, 0.01489480692722371, 0.01288473799574951, 0.011198475775133013, 0.010038128724558996, 0.009449322004070611, 0.009449322004070611, 0.010038128724558996, 0.011198475775133013, 0.01288473799574951, 0.01489480692722371, 0.01682916112649225, 0.018588416437931753, 0.02028149454107946, 0.021852691822297415, 0.02317845769263327, 0.024204824269097428, 0.024942382102965746, 0.025433018993558404, 0.02572289378519483, 0.02585156812403108, 0.02585156812403108, 0.02572289378519483, 0.025433018993558404, 0.024942382102965746, 0.024204824284620466, 0.02317845769263327, 0.022145827289685307, 0.02042805135939521, 0.018643586130194265, 0.01682916112649225, 0.014883062600264814, 0.013053141110424394, 0.011633781497279536, 0.01074148627431762, 0.010430230660255049, 0.01074148627431762, 0.011633781497279536, 0.013053141110424394, 0.014883062600264814, 0.01682916112649225, 0.018643586130194265, 0.02042805135939521, 0.022145827289685307, 0.023657583085668364, 0.02488053126382751, 0.025800253053947248, 0.02644560104894149, 0.026860034602867854, 0.02708309171483324, 0.027151657016416905, 0.02708309171483324, 0.026860034602867854, 0.026445601050353373, 0.025800253069470282, 0.02488053126382751, 0.023657583085668364, 0.022235037182788485, 0.02042805135939521, 0.018588416437931753, 0.016705110082744275, 0.014838711638586797, 0.013288096454131046, 0.01220434858125911, 0.011638354833823921, 0.011638354833823921, 0.01220434858125911, 0.013288096454131046, 0.014838711638586797, 0.016705110082744275, 0.018588416437931753, 0.02042805135939521, 0.022235037181376597, 0.023876272100392736, 0.02525037551288545, 0.02631760912831916, 0.027088755361362748, 0.027603533296746703, 0.027908712191780646, 0.028046898021049052, 0.028046898021049052, 0.027908712191780646, 0.027603533296746703, 0.027088755351484688, 0.02631760912831916, 0.02525037551288545, 0.023876272100392736, 0.022145827289685307, 0.02028149454107946, 0.01838247985011921, 0.016458622823396964, 0.014765683854799951, 0.01351871945764962, 0.012775745469630308, 0.012529422359386078, 0.012775745469630308, 0.01351871945764962, 0.014765683854799951, 0.016458622823396964, 0.01838247984870989, 0.02028149454107946, 0.022145827289685307, 0.023876272100392736, 0.02536675249494844, 0.02655738371046003, 0.027439093842301504, 0.028041035722972417, 0.02841200786241034, 0.028605543432288737, 0.028664313998241875, 0.028605543432288737, 0.02841200786241034, 0.028041035722972417, 0.027439093842301504, 0.026557383707638826, 0.02536675249494844, 0.02387627209898085, 0.021852691822297415, 0.01992937325132262, 0.017942818177434202, 0.016082846740739055, 0.014639725692955295, 0.013724810143582959, 0.013297636384243845, 0.013297636384243845, 0.013724810143582959, 0.014639725692955295, 0.016082846740739055, 0.017942818177434202, 0.01992937325132262, 0.021852691822297415, 0.023657583085668364, 0.02525037551288545, 0.026557383711871916, 0.02754913586481439, 0.02824061569970574, 0.028677500498590372, 0.02892070902513713, 0.029025523592854756, 0.029025523585797897, 0.02892070902513713, 0.028677500494354715, 0.02824061569970574, 0.027549135866226274, 0.026557383707638826, 0.02525037551288545, 0.023657583085668364, 0.021289405537333824, 0.019266421370540104, 0.017231759917201616, 0.015549856853502065, 0.014423942718867563, 0.013831808215880651, 0.013650790504842861, 0.013831808215880651, 0.014423942718867563, 0.015549856853502065, 0.017231759917201616, 0.019266421370540104, 0.021289405537333824, 0.02317845769263327, 0.02488053126382751, 0.02631760912831916, 0.027439093839480302, 0.028240615698293857, 0.028759317463963645, 0.02905994257120264, 0.029210986008471558, 0.029256067117124782, 0.029210986008471558, 0.029059942572617094, 0.028759317463963645, 0.02824061569970574, 0.027439093840892187, 0.02631760912831916, 0.02488053126382751, 0.02317845769263327, 0.020359502522962633, 0.018202365560353467, 0.016248082833591557, 0.014847319113605083, 0.01404488393495149, 0.013701533360467543, 0.013701533360467543, 0.01404488393495149, 0.014847319113605083, 0.016248082833591557, 0.018202365560353467, 0.020359502522962633, 0.022370099121114623, 0.024204824269097428, 0.02580025305253536, 0.027088755361362748, 0.028041035722972417, 0.028677500488709744, 0.02905994257402641, 0.029267261304526674, 0.029356079089374668, 0.029356079072439745, 0.02926726130593856, 0.029059942572617094, 0.02867750049012163, 0.028041035722972417, 0.027088755361362748, 0.02580025305253536, 0.024204824269097428, 0.022370099121114623, 0.018964037324507355, 0.01676775797378991, 0.015034223959459074, 0.013936123292691541, 0.013385589574354801, 0.013222604888781, 0.013385589574354801, 0.013936123292691541, 0.015034223959459074, 0.01676775797378991, 0.018964037324507355, 0.021147064770108075, 0.0231503150713325, 0.024942382102965746, 0.02644560104894149, 0.027603533296746703, 0.02841200786241034, 0.02892070902513713, 0.029210986008471558, 0.02935607908796278, 0.02939912316653883, 0.029356079090783985, 0.029210986008471558, 0.02892070902513713, 0.02841200786241034, 0.027603533296746703, 0.02644560104894149, 0.024942382102965746, 0.0231503150713325, 0.021147064770108075, 0.01713303089875586, 0.015069987998274524, 0.013596628277462183, 0.012743928196872886, 0.01237392710762056, 0.01237392710762056, 0.012743928196872886, 0.013596628277462183, 0.015069987998274524, 0.01713303089875586, 0.019454139208464893, 0.021649358382385377, 0.02366759427728574, 0.025433018993558404, 0.026860034602867854, 0.027908712191780646, 0.028605543432288737, 0.029025523585797897, 0.029256067143937765, 0.029356079089374668, 0.029356079086553463, 0.029256067143937765, 0.029025523584386013, 0.028605543432288737, 0.027908712191780646, 0.02686003460710351, 0.025433018993558404, 0.02366759427728574, 0.021649358382385377, 0.019454139208464893, 0.015027073432287454, 0.013163772621198347, 0.011913305022139525, 0.011243532635540964, 0.011035628677366563, 0.011243532636952849, 0.011913305022139525, 0.013163772621198347, 0.015027073432287454, 0.01732800024220794, 0.019694360589358625, 0.021934945102187603, 0.023980226181548533, 0.02572289378519483, 0.02708309171483324, 0.028046898021049052, 0.028664313998241875, 0.02902552359567596, 0.029210986008471558, 0.02926726130593856, 0.029210986008471558, 0.029025523584386013, 0.028664313998241875, 0.028046898021049052, 0.02708309171483324, 0.02572289378519483, 0.023980226181548533, 0.021934945102187603, 0.019694360589358625, 0.01732800024220794, 0.012746832373238334, 0.011071402674020946, 0.010002224995159091, 0.009496660797274951, 0.009496660797274951, 0.010002224995159091, 0.011071402674020946, 0.012746832373238334, 0.014934876376596327, 0.017369215082978437, 0.01977827285566793, 0.022076143474118026, 0.024139292094786883, 0.02585156812403108, 0.027151657016416905, 0.028046898021049052, 0.028605543432288737, 0.02892070902513713, 0.02905994257402641, 0.02905994257120264, 0.02892070902513713, 0.028605543432288737, 0.028046898021049052, 0.027151657016416905, 0.02585156812403108, 0.024139292094786883, 0.022076143474118026, 0.01977827285566793, 0.017369215082978437, 0.014934876376596327, 0.010344679818558007, 0.008836360637079085, 0.00793645979564411, 0.007637852288274728, 0.00793645979564411, 0.008836360637079085, 0.010344679818558007, 0.012404093212327083, 0.01483061319175465, 0.017321437948693633, 0.01978984714716384, 0.022128736159221365, 0.02418571534118722, 0.02585156812403108, 0.02708309171483324, 0.027908712191780646, 0.02841200786241034, 0.028677500494354715, 0.028759317463963645, 0.028677500502820894, 0.02841200786241034, 0.027908712191780646, 0.02708309171483324, 0.02585156812403108, 0.02418571534118722, 0.022128736159221365, 0.01978984714716384, 0.017321437948693633, 0.01483061319175465, 0.012404093212327083, 0.007853645516566367, 0.006502012537909789, 0.005803543732471961, 0.005803543732471961, 0.006502012537909789, 0.007853645516566367, 0.009791920945171492, 0.012183307197516747, 0.014740550396192733, 0.017272284193973794, 0.019786649819980306, 0.022128736159221365, 0.024139292094786883, 0.02572289378519483, 0.026860034602867854, 0.027603533296746703, 0.028041035722972417, 0.028240615708174484, 0.028240615692648883, 0.028041035722972417, 0.027603533296746703, 0.026860034602867854, 0.02572289378519483, 0.024139292094786883, 0.022128736159221365, 0.019786649819980306, 0.017272284193973794, 0.014740550396192733, 0.012183307197516747, 0.009791920945171492, 0.005299272889367739, 0.004179318519958506, 0.00379342830708924, 0.004179318519958506, 0.005299272889367739, 0.007090113076005102, 0.009439135467834685, 0.012090801183497172, 0.014701162449128703, 0.017272284193973794, 0.01978984714716384, 0.022076143474118026, 0.023980226181548533, 0.025433018993558404, 0.02644560104894149, 0.027088755361362748, 0.027439093840892187, 0.027549135866226274, 0.027439093840892187, 0.027088755361362748, 0.026445601050353373, 0.025433018993558404, 0.023980226181548533, 0.022076143474118026, 0.01978984714716384, 0.017272284193973794, 0.014701162449128703, 0.012090801183497172, 0.009439135467834685, 0.007090113076005102, 0.0030080286990708206, 0.0022516168853462543, 0.0022516168853462543, 0.0030080286990708206, 0.004494424933099573, 0.006654577493741669, 0.009310068611476237, 0.012090801183497172, 0.014740550396192733, 0.017321437948693633, 0.01977827285566793, 0.021934945102187603, 0.02366759427728574, 0.024942382102965746, 0.02580025305253536, 0.02631760912831916, 0.026557383725983066, 0.02655738371046003, 0.02631760912831916, 0.025800253068058398, 0.024942382102965746, 0.02366759427728574, 0.021934945102187603, 0.01977827285566793, 0.017321437948693633, 0.014740550396192733, 0.012090801183497172, 0.009310068611476237, 0.006654577493741669, 0.004494424933099573, 0.0013197032610667036, 0.0009624286188679017, 0.0013197032610667036, 0.0023998946753737717, 0.004211052927859079, 0.006654577493741669, 0.009439135467834685, 0.012183307197516747, 0.01483061319175465, 0.017369215082978437, 0.019694360589358625, 0.021649358382385377, 0.0231503150713325, 0.024204824269097428, 0.02488053126382751, 0.02525037551288545, 0.02536675249494844, 0.02525037551288545, 0.02488053126382751, 0.024204824269097428, 0.0231503150713325, 0.021649358382385377, 0.019694360589358625, 0.017369215082978437, 0.01483061319175465, 0.012183307197516747, 0.009439135467834685, 0.006654577493741669, 0.004211052927859079, 0.0023998946753737717, 0.0003276644660250489, 0.0003276644660250489, 0.001008906143675133, 0.0023998946753737717, 0.004494424933099573, 0.007090113076005102, 0.009791920945171492, 0.012404093212327083, 0.014934876376596327, 0.01732800024220794, 0.019454139208464893, 0.021147064770108075, 0.022370099121114623, 0.02317845769263327, 0.023657583085668364, 0.023876272100392736, 0.023876272100392736, 0.023657583085668364, 0.02317845769263327, 0.022370099121114623, 0.021147064770108075, 0.019454139208464893, 0.01732800024220794, 0.014934876376596327, 0.012404093212327083, 0.009791920945171492, 0.007090113076005102, 0.004494424933099573, 0.0023998946753737717, 0.001008906143675133])\n",
    "delta = np.array([0.0, 0.005541623615307856, 0.01943663001532059, 0.03815843253480722, 0.0606882120312946, 0.08851254231706207, 0.11262352593976033, 0.13075899586557682, 0.14592595011600196, 0.16081955557027783, 0.17970188538780008, 0.20295571167149262, 0.22237239074203075, 0.23533048963622605, 0.24255613160673306, 0.24485152496497165, 0.24255613160670464, 0.23533048963622605, 0.22237239074203075, 0.20295571167145, 0.1797018853878285, 0.16081955557027072, 0.14592595011597354, 0.13075899586556972, 0.11262352593979585, 0.08851254231706207, 0.06068821203162145, 0.038158432534842746, 0.019436630015356116, 0.005541623615314961, 0.005541623615314961, 0.01331536400725497, 0.026866349109880616, 0.04561181437118478, 0.07078901159886186, 0.097001190583768, 0.11689842506950754, 0.13270331901448884, 0.14591871007265667, 0.15834458933661466, 0.17380584828498513, 0.19338513562863824, 0.2120728816228592, 0.22341833236870912, 0.22853662554950915, 0.2285088882561297, 0.2234183323688157, 0.212072881622845, 0.1933851356287093, 0.17380584828498513, 0.15834458933660756, 0.1459187100726922, 0.13270331901449595, 0.11689842506949333, 0.097001190583768, 0.07078901159886186, 0.0456118143712132, 0.026866349109866405, 0.013315364007198127, 0.005541623615314961, 0.019436630015306378, 0.026866349109880616, 0.04005475255581814, 0.060689274713794816, 0.0854178570514108, 0.10542699280703971, 0.1221348536247433, 0.13608731348548986, 0.14743483944548075, 0.1576976308827085, 0.1697128415987521, 0.18368435752065437, 0.19836540958823434, 0.2090258538200942, 0.21233186398202974, 0.20902585382006578, 0.19836540958827698, 0.18368435752063306, 0.1697128415987592, 0.15769763088269428, 0.14743483944548075, 0.13608731348551828, 0.12213485362440224, 0.10542699280705392, 0.0854178570514108, 0.060689274713794816, 0.04005475255581814, 0.026866349109880616, 0.019436630015306378, 0.016933037985893407, 0.038158432534856956, 0.04561181437119899, 0.060689274713794816, 0.08120115836113939, 0.0985535759678342, 0.1136411208109962, 0.12704318624997768, 0.13834820487858224, 0.1472848113428853, 0.15479230638712238, 0.16284388405492933, 0.17061694797637017, 0.1780824270538659, 0.18454289853671924, 0.18454289853670502, 0.1780824270538659, 0.1706169479749704, 0.1628438840549009, 0.15479230638761976, 0.14728481134284976, 0.13834820487859645, 0.12704318624994215, 0.1136411208109962, 0.0985535759678342, 0.08120115836112518, 0.060689274713794816, 0.045611814371206094, 0.038158432534856956, 0.03496863398257943, 0.03496863398256522, 0.06068821203132302, 0.07078901159886186, 0.0854178570514108, 0.0985535759678342, 0.11024942418015371, 0.1209387863482192, 0.13037694682464007, 0.13781003362569777, 0.1430205577629522, 0.14663063092552875, 0.14968567222995688, 0.1508396907782128, 0.14868200566931478, 0.14648675448955828, 0.14868200566931478, 0.1508396907782128, 0.1496856722299995, 0.14663063092551454, 0.1430205577629522, 0.13781003362566935, 0.13037694682461165, 0.1209387863482192, 0.1102494241801466, 0.09855357596785552, 0.0854178570514108, 0.07078901159886186, 0.060688212031408284, 0.05596552064464788, 0.05455642334713673, 0.05596552064464788, 0.08851254231704786, 0.0970011905837822, 0.10542699280705392, 0.11364112081096778, 0.1209387863482192, 0.12704355822202018, 0.13150759263152167, 0.13377651899799758, 0.13351709855599836, 0.13146397985184421, 0.12804739193582293, 0.12174453412077924, 0.11797663476669129, 0.1179766347666984, 0.12174453412078634, 0.12804739193582293, 0.13146397985184421, 0.13351709855594152, 0.13377651899798337, 0.13150759263147904, 0.1270435582220628, 0.1209387863482192, 0.1136411208109962, 0.1054269928070255, 0.0970011905837822, 0.08851254231706918, 0.08036626481417386, 0.07604824987025438, 0.07604824987024728, 0.08036626481417386, 0.11262352593978164, 0.11689842506949333, 0.1221348536243454, 0.12704318624995636, 0.13037694682461165, 0.13150759263147904, 0.12999248242272898, 0.12562595829174938, 0.11823345924230466, 0.10802295303169274, 0.09968008144792861, 0.09656462253290954, 0.09594391333588703, 0.09656462253290954, 0.09968008144792861, 0.10802295303169274, 0.11823345924230466, 0.1256259582917636, 0.12999248242270056, 0.1315075926315643, 0.13037694682456902, 0.12704318624994926, 0.12213485362481435, 0.11689842506950754, 0.11262352593979585, 0.10818940005012223, 0.10241054554438733, 0.09954551522132249, 0.1024105455442168, 0.10818940005012223, 0.13075899586557682, 0.13270331901449595, 0.13608731348548986, 0.13834820487858224, 0.13781003362571198, 0.1337765189980047, 0.12562595829174228, 0.11331183964553304, 0.0963336603516467, 0.08305319680786738, 0.0782538069812162, 0.07715372057158731, 0.07715372057154468, 0.07825380698126594, 0.08305319680786738, 0.0963336603516467, 0.11331183964554015, 0.1256259582917778, 0.13377651899797627, 0.13781003362571198, 0.13834820487859645, 0.13608731348547565, 0.13270331901448884, 0.1307589958655342, 0.12996798226794226, 0.1298695679650237, 0.13017196439994194, 0.13017196439994194, 0.1298695679650521, 0.12996798226791384, 0.14592595011597354, 0.14591871007267798, 0.14743483944548785, 0.1472848113428853, 0.1430205577629522, 0.1335170985559131, 0.11823345924230466, 0.0963336603516467, 0.07673142302581226, 0.06662538303910992, 0.06274130654364285, 0.061801329041863085, 0.06274130654362153, 0.06662538303911703, 0.0767314230258549, 0.0963336603516467, 0.11823345924230466, 0.1335170985559131, 0.1430205577629593, 0.1472848113428853, 0.14743483944548075, 0.14591871007267798, 0.14592595011597354, 0.14803652963334457, 0.1520827241579994, 0.15680287801059478, 0.15862805959559978, 0.15680287801059478, 0.1520827241580065, 0.14803652963333036, 0.16081955557027072, 0.15834458933662887, 0.1576976308827227, 0.1547923063876837, 0.14663063092550033, 0.13146397985184421, 0.10802295303169274, 0.08305319680786738, 0.06662538303913834, 0.05714791668831509, 0.05273872428253412, 0.05273872428253412, 0.057147916688293776, 0.06662538303912413, 0.08305319680786738, 0.10802295303169274, 0.13146397985184421, 0.14663063092550743, 0.15479230638744923, 0.1576976308827227, 0.15834458933660756, 0.1608195555702494, 0.1660858553276796, 0.1727832363621502, 0.1773777556823788, 0.17955776385486644, 0.17955776385476696, 0.17737775568241432, 0.17278323636013226, 0.16608585532771514, 0.1797018853878143, 0.17380584828499934, 0.1697128415987308, 0.16284388405490802, 0.14968567222996398, 0.12804739193582293, 0.09968008144792861, 0.07825380698125883, 0.06274130654362864, 0.052738724282562544, 0.04908088528014787, 0.052738724282527016, 0.06274130654362864, 0.07825380698135831, 0.09968008144792861, 0.12804739193582293, 0.1496856722299711, 0.16284388405492223, 0.1697128415987308, 0.17380584828497803, 0.17970188538778586, 0.187787002826461, 0.1938092073899753, 0.19748976356095227, 0.19966471494916505, 0.20053351038428957, 0.19966471494916505, 0.19748976356096648, 0.19380920738998242, 0.18778700282643257, 0.20295571167143578, 0.19338513562851034, 0.18368435752066148, 0.17061694797610727, 0.1508396907782199, 0.12174453412079345, 0.09656462253289533, 0.07715372057161574, 0.06180132904185598, 0.05273872428253412, 0.052738724282527016, 0.06180132904185598, 0.07715372057162284, 0.0965646225328669, 0.12174453412085029, 0.1508396907782128, 0.17061694797490645, 0.18368435752060464, 0.19338513562864534, 0.20295571167145, 0.21056922427537472, 0.21580737042108922, 0.21943396764223166, 0.22183205361282887, 0.22334916339339372, 0.22334916339340793, 0.22183205361267255, 0.21943396764221745, 0.21580737042108922, 0.21056922427537472, 0.22237239074203075, 0.212072881622845, 0.19836540958911542, 0.1780824270538659, 0.14868200566931478, 0.11797663476669129, 0.09594391333588703, 0.07715372057155889, 0.06274130654361443, 0.05714791668830799, 0.06274130654365706, 0.07715372057161574, 0.09594391333588703, 0.11797663476667708, 0.14868200566931478, 0.1780824270538659, 0.19836540958841908, 0.212072881622845, 0.22237239074201653, 0.23091343202591474, 0.23737736077523408, 0.24222787361999565, 0.24575740357896336, 0.2481491165990377, 0.24908491977633673, 0.2481491165990377, 0.24575740357896336, 0.24222787362003828, 0.2373773607752412, 0.23091343202591474, 0.23533048963622605, 0.22341833236872333, 0.2090258538200871, 0.18454289853674055, 0.14648675448955828, 0.11797663476671261, 0.0965646225328527, 0.0782538069814791, 0.06662538303914545, 0.06662538303911703, 0.07825380698123752, 0.09656462253292375, 0.11797663476671261, 0.14648675448955828, 0.18454289853671213, 0.20902585382007288, 0.22341833236872333, 0.23533048963621184, 0.24645629091583743, 0.25604565034051063, 0.2638732773176926, 0.26973813329233565, 0.27401119238007254, 0.2761782139437159, 0.2761782139437372, 0.2740111923800441, 0.2697381332930391, 0.26387327731774946, 0.2560437420972903, 0.24645629091583032, 0.24255613160671885, 0.22853662554949494, 0.21233186398203685, 0.18454289853673345, 0.14868200566931478, 0.12174453412077924, 0.09968008144792861, 0.08305319680786738, 0.07673142302584068, 0.08305319680786738, 0.09968008144792861, 0.12174453412078634, 0.14868200566930057, 0.18454289853674055, 0.21233186398203685, 0.22853662554940968, 0.24255613160671885, 0.25639450235455996, 0.26952461106114356, 0.2812832166459742, 0.2910621250644141, 0.2984966838190388, 0.30295937593618305, 0.3043517018280042, 0.30295937593642464, 0.2984966838189962, 0.2910621250665457, 0.2812561927597841, 0.26952461106114356, 0.2563945023546381, 0.2448515249650356, 0.22853662554950205, 0.20902585382008, 0.1780824270538659, 0.150839690778227, 0.12804739193582293, 0.10802295303169274, 0.0963336603516467, 0.0963336603516467, 0.10802295303169274, 0.12804739193582293, 0.1508396907782128, 0.1780824270538659, 0.20902585382007288, 0.22853662554948073, 0.24485152496498586, 0.2611668393311035, 0.27741840435355414, 0.2928239257262675, 0.3066522734923396, 0.3181877397912416, 0.3263085075333123, 0.33015680568130534, 0.3301568056812414, 0.3263085075333194, 0.3181877397904458, 0.30664319254115924, 0.2928239257262817, 0.27741840435358256, 0.2611668393311035, 0.24255613160673306, 0.2234183323686949, 0.19836540958928595, 0.17061694797501303, 0.14968567222995688, 0.13146397985183, 0.11823345924230466, 0.11331183964553304, 0.11823345924230466, 0.13146397985184421, 0.1496856722299853, 0.17061694797521199, 0.19836540958828408, 0.2234183323686949, 0.24255613160671885, 0.2611668393311035, 0.279973056724387, 0.2984451507647563, 0.3158198253127793, 0.3311766121494486, 0.34318151446929335, 0.350310005488808, 0.35268288499335654, 0.35031000548877955, 0.34318151446927914, 0.3311766121494699, 0.31581982531142216, 0.29845062339137485, 0.27997305672484174, 0.2611668393310822, 0.23533048963622605, 0.2120728816228592, 0.18368435752066148, 0.16284388405492933, 0.14663063092551454, 0.1335170985559344, 0.1256259582917636, 0.1256259582917778, 0.1335170985559202, 0.14663063092553585, 0.16284388405492223, 0.18368435752064016, 0.212072881622845, 0.23533048963622605, 0.2563945023546381, 0.27741840435354703, 0.2984451507677903, 0.3188109893112312, 0.3374737327362425, 0.35293433027231913, 0.3633130873142605, 0.36816090908996557, 0.3681693649139106, 0.36331308731422496, 0.35294496236161166, 0.3374664592610941, 0.3188109893106059, 0.2984506233914459, 0.27741840435357545, 0.25639450235455286, 0.22237239074203075, 0.19338513562868087, 0.1697128415987379, 0.15479230638745634, 0.1430205577629593, 0.13377651899797627, 0.12999248242270767, 0.13377651899797627, 0.1430205577629593, 0.15479230638710817, 0.1697128415987379, 0.19338513562868798, 0.22237239074203075, 0.2464562909158161, 0.26952461106113645, 0.2928239257262817, 0.3158198253150317, 0.3374664592586072, 0.35610344527064797, 0.3694666319537703, 0.3768419601213395, 0.37915506589962433, 0.3768419601215811, 0.36946663195114837, 0.3561034452706551, 0.3374731530612394, 0.3158198253129285, 0.2928239257262817, 0.26952461106114356, 0.24645629091585164, 0.20295571167145, 0.17380584828498513, 0.15769763088273692, 0.14728481134286397, 0.13781003362568356, 0.13150759263150746, 0.13150759263150746, 0.13781003362571198, 0.14728481134285687, 0.1576976308827298, 0.17380584828497803, 0.2029557116714784, 0.23091343202591474, 0.25604565034055327, 0.2812832166455408, 0.3066522734923325, 0.3311766121494628, 0.3529378229744111, 0.3694666319582183, 0.3795699586983119, 0.3842341223084702, 0.38421655579884373, 0.3795699587031862, 0.36946663195582374, 0.35293782297470244, 0.331176612149477, 0.3066522734923396, 0.2812832166456758, 0.25604565034055327, 0.23091343202590764, 0.1797018853878143, 0.15834458933661466, 0.14743483944548075, 0.13834820487861776, 0.13037694682461165, 0.1270435582220557, 0.13037694682458323, 0.13834820487858224, 0.14743483944548075, 0.15834458933662177, 0.17970188538777876, 0.21056922427537472, 0.23737736077521276, 0.2638732773176571, 0.2910645412781463, 0.3181877397910853, 0.34318151446927914, 0.3633130873140118, 0.3768419601212898, 0.3842056278518058, 0.3865334761953534, 0.3842056278539445, 0.37684196012152427, 0.3633130873143102, 0.34318151446929335, 0.31818773979050263, 0.2910645412785726, 0.26387327731774235, 0.23737736077522698, 0.2105692242753605, 0.16081955557026362, 0.1459187100726922, 0.13608731348544723, 0.1270431862499919, 0.12093878634820499, 0.12093878634821209, 0.12704318624997057, 0.13608731348551828, 0.14591871007267798, 0.1608195555702423, 0.1877870028264681, 0.21580737042116027, 0.2422278736200525, 0.2697381332921367, 0.29849668381930883, 0.3263085075330707, 0.3503100054887369, 0.36816936491372587, 0.37911569858842853, 0.3842341223084631, 0.38420562785151446, 0.3791156985882509, 0.3681693649132285, 0.35031000548879376, 0.3263085075332697, 0.298514806184464, 0.26973813329156826, 0.24222787362002407, 0.2158073704211887, 0.18778700282645389, 0.14592595011598775, 0.13270331901448884, 0.12213485362466514, 0.11364112081101041, 0.1102494241801395, 0.11364112081096778, 0.12213485362437382, 0.13270331901448174, 0.14592595011600196, 0.16608585532769382, 0.19380920739000373, 0.21943396764222456, 0.24575740357897047, 0.27401119238006544, 0.302959375936112, 0.33015680568145456, 0.3526828849933068, 0.36815601617162486, 0.37684196012139637, 0.37956995870125354, 0.3768419601215669, 0.36816936491187846, 0.3526828849933068, 0.330156805681284, 0.3029593759361262, 0.27401119238007254, 0.24575740357896336, 0.21943396764223166, 0.1938092073899753, 0.1660858553276654, 0.13075899586556972, 0.11689842506948622, 0.10542699280701129, 0.0985535759678342, 0.0985535759678342, 0.1054269928070326, 0.11689842506950754, 0.13075899586557682, 0.14803652963334457, 0.1727832363595354, 0.19748976356095937, 0.22183205361267255, 0.2481491165990235, 0.2761782139437088, 0.3043517018277839, 0.3301568056813977, 0.35031000548875113, 0.3633130873142676, 0.3694666319579625, 0.36946663195402607, 0.3633130873142747, 0.3503100054888364, 0.3301568056813693, 0.30435170182845894, 0.2761782139437159, 0.2481491165990377, 0.2218320536127436, 0.19748976356095227, 0.17278323636118387, 0.14803652963333036, 0.11262352593976743, 0.097001190583768, 0.0854178570514108, 0.0812011583611536, 0.0854178570514108, 0.097001190583768, 0.11262352593976743, 0.12996798226795647, 0.1520827241580065, 0.17737775568241432, 0.19966471494916505, 0.22334916339341504, 0.24908491977631542, 0.27617821394380115, 0.3029593759366236, 0.32630850753324125, 0.34318151446927914, 0.35294496236149087, 0.35610344527063376, 0.3529266892192737, 0.34318151446928624, 0.3263085075331986, 0.3029593759362825, 0.2761782139437159, 0.2490849197762941, 0.22334916339339372, 0.19966471494916505, 0.17737775568241432, 0.1520827241580065, 0.12996798226792805, 0.08851254231704786, 0.07078901159886186, 0.060689274713794816, 0.060689274713794816, 0.07078901159886186, 0.08851254231707628, 0.10818940005012223, 0.12986956796500237, 0.15680287801056636, 0.17955776385476696, 0.20053351038428247, 0.2233491633933795, 0.2481491165990235, 0.27401119238007254, 0.2984966838195078, 0.31818773979040316, 0.331176612149477, 0.3374568306061221, 0.3374700402644564, 0.3311766121494628, 0.3181877397905808, 0.29849668381974226, 0.2740111923800441, 0.2481491165990377, 0.22334916339343636, 0.20053351038428957, 0.17955776385478828, 0.15680287801056636, 0.129869567965045, 0.10818940005011513, 0.06068821203136565, 0.0456118143712132, 0.04005475255581814, 0.04561181437117057, 0.06068821203162145, 0.08036626481417386, 0.10241054554465734, 0.13017196439993484, 0.15862805959559267, 0.17955776385478828, 0.19966471494916505, 0.2218320536125873, 0.24575740357897047, 0.269738133292563, 0.2910645412784305, 0.3066522734923325, 0.31581982531282904, 0.31881098931053486, 0.3158198253129001, 0.3066522734923183, 0.29106212506582096, 0.2697381332918667, 0.24575740357897757, 0.22183205361280045, 0.19966471494916505, 0.17955776385477407, 0.15862805959559978, 0.13017196439993484, 0.10241054554416706, 0.08036626481417386, 0.038158432534764586, 0.02686634910992325, 0.02686634910992325, 0.03815843253483564, 0.055965520644626565, 0.07604824987024017, 0.09954551522126565, 0.13017196439993484, 0.15680287801055925, 0.17737775568241432, 0.19748976356095227, 0.21943396764225298, 0.2422278736200667, 0.26387327731772814, 0.2812832166455621, 0.2928239257262817, 0.2984516331511742, 0.2984451507659145, 0.2928239257262675, 0.2812561927627115, 0.26387327731775656, 0.24222787362003828, 0.21943396764224588, 0.19748976356096648, 0.17737775568237168, 0.15680287801059478, 0.13017196439994194, 0.09954551522132249, 0.07604824987022596, 0.055965520644626565, 0.019436630015306378, 0.013315364007297603, 0.019436630015306378, 0.03496863398257943, 0.05455642334713673, 0.07604824987024017, 0.10241054554417417, 0.12986956796501659, 0.1520827241580207, 0.17278323635773063, 0.1938092073899611, 0.2158073704211887, 0.23737736077522698, 0.25604565034051063, 0.26952461106114356, 0.27741840435356835, 0.2799730567250549, 0.27741840435355414, 0.26952461106114356, 0.25604565034053905, 0.23737736077521987, 0.21580737042112474, 0.1938092073899682, 0.17278323636047332, 0.1520827241580065, 0.1298695679650237, 0.10241054554415996, 0.07604824987025438, 0.05455642334713673, 0.03496863398257233, 0.005541623615314961, 0.005541623615314961, 0.016933037985893407, 0.03496863398256522, 0.05596552064464788, 0.08036626481413833, 0.10818940005012223, 0.12996798226794226, 0.14803652963331615, 0.1660858553276796, 0.187787002826461, 0.21056922427537472, 0.23091343202591474, 0.24645629091584453, 0.2563945023545955, 0.2611668393310964, 0.2611668393310964, 0.2563945023546097, 0.24645629091583032, 0.23091343202594317, 0.21056922427537472, 0.1877870028264681, 0.16608585532770803, 0.14803652963334457, 0.12996798226791384, 0.10818940005012223, 0.08036626481415965, 0.055965520644612354, 0.03496863398257233, 0.016933037985893407])\n",
    "\n",
    "gamma = am.defect.GammaSurface(a1vect=a1vect, a2vect=a2vect, a1=a1, a2=a2,\n",
    "                               E_gsf=E_gsf, box=box, delta=delta)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2. Class attributes\n",
    "\n",
    "The GammaSurface class has the following attributes for the data\n",
    "\n",
    "- **a1vect, a2vect** the two shifting vectors as given.\n",
    "- **box** the unit cell box as given.\n",
    "- **planenormal** a Cartesian vector normal to the fault plane.\n",
    "- **data** a pandas.DataFrame tabulating the measured stacking fault data.  The data columns are\n",
    "    - **a1** fractional coordinates along the a1vect.\n",
    "    - **a2** fractional coordinates along the a2vect.\n",
    "    - **E_gsf** generalized stacking fault energies measured for each (a1, a2) fault shift.\n",
    "    - **delta** (optional) relaxation distances measured for each (a1, a2) fault shift."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "gamma.a1vect -> [ 0.  -0.5  0.5]\n",
      "gamma.a2vect -> [ 0.5 -0.5  0. ]\n",
      "gamma.planenormal -> [0.57735027 0.57735027 0.57735027]\n",
      "gamma.box ->\n",
      "avect =  [ 4.045,  0.000,  0.000]\n",
      "bvect =  [ 0.000,  4.045,  0.000]\n",
      "cvect =  [ 0.000,  0.000,  4.045]\n",
      "origin = [ 0.000,  0.000,  0.000]\n"
     ]
    }
   ],
   "source": [
    "print('gamma.a1vect ->', gamma.a1vect)\n",
    "print('gamma.a2vect ->', gamma.a2vect)\n",
    "print('gamma.planenormal ->', gamma.planenormal)\n",
    "print('gamma.box ->')\n",
    "print(gamma.box)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a1</th>\n",
       "      <th>a2</th>\n",
       "      <th>E_gsf</th>\n",
       "      <th>delta</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>0.033333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000328</td>\n",
       "      <td>0.005542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>0.066667</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001320</td>\n",
       "      <td>0.019437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.003008</td>\n",
       "      <td>0.038158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0.133333</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.005299</td>\n",
       "      <td>0.060688</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>895</td>\n",
       "      <td>0.833333</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.009792</td>\n",
       "      <td>0.108189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>896</td>\n",
       "      <td>0.866667</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.007090</td>\n",
       "      <td>0.080366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>897</td>\n",
       "      <td>0.900000</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.004494</td>\n",
       "      <td>0.055966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>898</td>\n",
       "      <td>0.933333</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.002400</td>\n",
       "      <td>0.034969</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>899</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.966667</td>\n",
       "      <td>0.001009</td>\n",
       "      <td>0.016933</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>900 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           a1        a2     E_gsf     delta\n",
       "0    0.000000  0.000000  0.000000  0.000000\n",
       "1    0.033333  0.000000  0.000328  0.005542\n",
       "2    0.066667  0.000000  0.001320  0.019437\n",
       "3    0.100000  0.000000  0.003008  0.038158\n",
       "4    0.133333  0.000000  0.005299  0.060688\n",
       "..        ...       ...       ...       ...\n",
       "895  0.833333  0.966667  0.009792  0.108189\n",
       "896  0.866667  0.966667  0.007090  0.080366\n",
       "897  0.900000  0.966667  0.004494  0.055966\n",
       "898  0.933333  0.966667  0.002400  0.034969\n",
       "899  0.966667  0.966667  0.001009  0.016933\n",
       "\n",
       "[900 rows x 4 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gamma.data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.3. Saving and loading data model\n",
    "\n",
    "The GammaSurface.model() method allows for the saving and loading of a GammaSurface object's data as a JSON/XML data model.\n",
    "\n",
    "Parameters\n",
    "        \n",
    "- **model** (*str, file-like object or DataModelDict, optional*) XML/JSON content to extract gamma surface energy from. If not given, model content will be generated.\n",
    "- **length_unit** (*str, optional*) Units to report delta displacement values in when a new model is generated. Default value is 'angstrom'.\n",
    "- **energyperarea_unit** (*str, optional*) Units to report fault energy values in when a new model is generated.  Default value is 'mJ/m^2'.\n",
    "        \n",
    "Returns\n",
    "\n",
    "(*DataModelDict*) A data model containing the stacking fault data of the GammaSurface object.  Returned if model is not given."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.3.1. Save data model\n",
    "\n",
    "Calling GammaSurface.model() without supplying the 'model' parameter will return  a data model of the content."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = gamma.model()\n",
    "with open('gamma.json', 'w') as f:\n",
    "    model.json(fp=f)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 3.3.2. Load data model\n",
    "\n",
    "The saved data can then be loaded by using the 'model' parameter when initializing a GammaSurface, or with the GammaSurface.model() method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "gamma = am.defect.GammaSurface(model='gamma.json')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Plotting methods<a id='section4'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.1. **E_gsf_line_plot()** \n",
    "\n",
    "Generates a line plot for the interpolated generalized stacking fault energy along a specified vector in the (a1, a2) plane.\n",
    "        \n",
    "Parameters\n",
    "        \n",
    "- **vect** (*numpy.array, optional*) Vector to plot the gsf along.  If box is set, this vect will be a lattice vector, otherwise it will be a Cartesian vector.  Must be in the plane defined by the GammaSurface object's a1vect and a2vect vectors.  Default value will use the set a1vect.\n",
    "- **num** (*int, optional*) The number of points to evaluate the generalized stacking fault energy for.  Default value is 100 if smooth is True, otherwise is number of unique a1 values from 0 to 1.\n",
    "- **smooth** (*bool, optional*) If True (default), then plot shows smooth interpolated values. If False, plot shows nearest raw data values.\n",
    "- **length_unit** (*str, optional*) The unit of length to display the x-axis coordinates in. Default value is 'Å'.\n",
    "- **energyperarea_unit** (*str, optional*) The unit of energy per area to display the stacking fault energies in. Default value is 'eV/Å^2'.\n",
    "- **figsize** (*tuple, optional*) The x,y size of the figure to return.  Default value is (10, 6).\n",
    "- **fig** (*matplotlib.figure, optional*) An existing figure object to add the new plot to.  If not given, a new figure is generated.\n",
    "- **\\*\\*kwargs** (*dict, optional*) Additional keywords are passed into the underlying  matplotlib.pyplot.plot(). This allows control of such things like line color, style, etc.\n",
    "        \n",
    "Returns\n",
    "\n",
    "(*matplotlib.figure*)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If vect is not given, will use a1vect"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generate RBF interpolated plot\n",
    "fig = gamma.E_gsf_line_plot(fmt='k-', label='RBF')\n",
    "\n",
    "# Generate measured (nearest) plot and append to above\n",
    "fig = gamma.E_gsf_line_plot(smooth=False, fmt='k:o', fig=fig, label='measured')\n",
    "\n",
    "# Additional plot manipulations\n",
    "plt.legend(loc=2, fontsize='x-large')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The important direction for fcc {111} stacking faults is a/2&lt;112&gt;, and energy values in mJ/m^2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generate RBF interpolated plot\n",
    "vect = np.array([1, 1, -2]) / 2\n",
    "fig = gamma.E_gsf_line_plot(vect=vect, fmt='k-', energyperarea_unit='mJ/m^2', label='RBF')\n",
    "\n",
    "# Generate measured (nearest) plot and append to above\n",
    "fig = gamma.E_gsf_line_plot(vect=vect, smooth=False, fmt='k:o', \n",
    "                            energyperarea_unit='mJ/m^2', fig=fig, label='measured')\n",
    "\n",
    "# Additional plot manipulations\n",
    "plt.legend(loc=2, fontsize='x-large')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.2. **delta_line_plot()** \n",
    "\n",
    "Generates a line plot for the interpolated relaxation distances along a specified vector in the (a1, a2) plane.\n",
    "        \n",
    "Parameters\n",
    "        \n",
    "- **vect** (*numpy.array, optional*) Vector to plot the gsf along.  If box is set, this vect will be a lattice vector, otherwise it will be a Cartesian vector.  Must be in the plane defined by the GammaSurface object's a1vect and a2vect vectors.  Default value will use the set a1vect.\n",
    "- **num** (*int, optional*) The number of points to evaluate the generalized stacking fault energy for.  Default value is 100 if smooth is True, otherwise is number of unique a1 values from 0 to 1.\n",
    "- **smooth** (*bool, optional*) If True (default), then plot shows smooth interpolated values. If False, plot shows nearest raw data values.\n",
    "- **length_unit** (*str, optional*) The unit of length to display the x-axis coordinates in. Default value is 'Å'.\n",
    "- **figsize** (*tuple, optional*) The x,y size of the figure to return.  Default value is (10, 6).\n",
    "- **fig** (*matplotlib.figure, optional*) An existing figure object to add the new plot to.  If not given, a new figure is generated.\n",
    "- **\\*\\*kwargs** (*dict, optional*) Additional keywords are passed into the underlying  matplotlib.pyplot.plot(). This allows control of such things like line color, style, etc.\n",
    "        \n",
    "Returns\n",
    "\n",
    "(*matplotlib.figure*)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If vect is not given, will use a1vect"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generate RBF interpolated plot\n",
    "fig = gamma.delta_line_plot(fmt='k-', label='RBF')\n",
    "\n",
    "# Generate measured (nearest) plot and append to above\n",
    "fig = gamma.delta_line_plot(smooth=False, fmt='k:o', fig=fig, label='measured')\n",
    "\n",
    "# Additional plot manipulations\n",
    "plt.legend(loc=2, fontsize='x-large')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The important direction for fcc {111} stacking faults is a/2&lt;112&gt;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generate RBF interpolated plot\n",
    "vect = np.array([1, 1, -2]) / 2\n",
    "fig = gamma.delta_line_plot(vect=vect, fmt='k-', label='RBF')\n",
    "\n",
    "# Generate measured (nearest) plot and append to above\n",
    "fig = gamma.delta_line_plot(vect=vect, smooth=False, fmt='k:o', fig=fig, label='measured')\n",
    "\n",
    "# Additional plot manipulations\n",
    "plt.legend(loc=2, fontsize='x-large')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.3. **E_gsf_surface_plot()** \n",
    "\n",
    "Creates a 2D surface plot from the stacking fault energy values.\n",
    "        \n",
    "Parameters\n",
    "        \n",
    "- **normalize** (*bool, optional*) Flag indicating if axes are Cartesian (False, default) or normalized by a1, a2 vectors (True).\n",
    "- **smooth** (*bool, optional*) If True (default), then plot shows smooth interpolated values. If False, plot shows nearest raw data values.\n",
    "- **a1vect** (*np.array, optional*) Crystal vector for the a1 vector to use for plotting.  Default value of None uses the saved a1vect.\n",
    "- **a2vect** (*np.array, optional*) Crystal vector for the a2 vector to use for plotting.  Default value of None uses the saved a2vect.\n",
    "- **xvect** (*numpy.array, optional*) Crystal vector to align with the plotting x-axis for  non-normalized plots.  If not given, this is taken as the Cartesian of a1vect.\n",
    "- **length_unit** (*str, optional*) The unit of length to display non-normalized axes values in. Default value is 'Å'.\n",
    "- **energyperarea_unit** (*str, optional*) The unit of energy per area to display the stacking fault energies in. Default value is 'eV/Å^2'.\n",
    "- **numx** (*int, optional*) The number of plotting points to use along the x-axis.  Default value is 100.\n",
    "- **numy** (*int, optional*) The number of plotting points to use along the y-axis.  Default value is 100.       \n",
    "- **figsize** (*tuple or None, optional*) The figure's x,y dimensions.  If None (default), the values are scaled such that the x,y spacings are approximately equal, and the larger of the two values is set to 10.\n",
    "- **\\*\\*kwargs** (*dict, optional*) Additional keywords are passed into the underlying matplotlib.pyplot.pcolormesh(). This allows control of such things like the colormap (cmap).\n",
    "            \n",
    "Returns\n",
    "        \n",
    "(*matplotlib.figure*)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Default setting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 846x415.692 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = gamma.E_gsf_surface_plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plotting actual measured values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 846x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = gamma.E_gsf_surface_plot(smooth=False, normalize=True, cmap='gray')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Specifying a different a1vect and a2vect to use for plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 846x415.692 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_a1vect = np.array([1, 1, -2]) / 2\n",
    "plot_a2vect = np.array([1,-1, 0]) / 2\n",
    "\n",
    "fig = gamma.E_gsf_surface_plot(a1vect=plot_a1vect, a2vect=plot_a2vect, energyperarea_unit='mJ/m^2', cmap='jet')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.4. **delta_surface_plot()** \n",
    "\n",
    "Creates a 2D surface plot from the relaxation distance values.\n",
    "        \n",
    "Parameters\n",
    "        \n",
    "- **normalize** (*bool, optional*) Flag indicating if axes are Cartesian (False, default) or normalized by a1, a2 vectors (True).\n",
    "- **smooth** (*bool, optional*) If True (default), then plot shows smooth interpolated values. If False, plot shows nearest raw data values.\n",
    "- **a1vect** (*np.array, optional*) Crystal vector for the a1 vector to use for plotting.  Default value of None uses the saved a1vect.\n",
    "- **a2vect** (*np.array, optional*) Crystal vector for the a2 vector to use for plotting.  Default value of None uses the saved a2vect.\n",
    "- **xvect** (*numpy.array, optional*) Crystal vector to align with the plotting x-axis for  non-normalized plots.  If not given, this is taken as the Cartesian of a1vect.\n",
    "- **length_unit** (*str, optional*) The unit of length to display non-normalized axes values in. Default value is 'Å'.\n",
    "- **numx** (*int, optional*) The number of plotting points to use along the x-axis.  Default value is 100.\n",
    "- **numy** (*int, optional*) The number of plotting points to use along the y-axis.  Default value is 100.       \n",
    "- **figsize** (*tuple or None, optional*) The figure's x,y dimensions.  If None (default), the values are scaled such that the x,y spacings are approximately equal, and the larger of the two values is set to 10.\n",
    "- **\\*\\*kwargs** (*dict, optional*) Additional keywords are passed into the underlying matplotlib.pyplot.pcolormesh(). This allows control of such things like the colormap (cmap).\n",
    "            \n",
    "Returns\n",
    "        \n",
    "(*matplotlib.figure*)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Default setting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 846x415.692 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = gamma.delta_surface_plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plotting actual measured values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 846x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = gamma.delta_surface_plot(smooth=False, normalize=True, cmap='gray')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Specifying a different a1vect and a2vect to use for plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 846x415.692 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_a1vect = np.array([1, 1, -2]) / 2\n",
    "plot_a2vect = np.array([1,-1, 0]) / 2\n",
    "\n",
    "fig = gamma.delta_surface_plot(a1vect=plot_a1vect, a2vect=plot_a2vect, cmap='jet')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5. Minimum energy slip path<a id='section5'></a>\n",
    "\n",
    "*Added version 1.3.7*\n",
    "\n",
    "The path() and build_path() methods allow for the construction of atomman.mep.Path objects where the energy function associated with the path coordinates is automatically set using the generalized stacking fault energy.  path() allows for all 2D coordinates along the path to be specified, while build_path() allows for a path to be constructed based only on the endpoints and optionally one intermediate junction point.\n",
    "\n",
    "__Documentation coming soon...__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Utility methods<a id='section6'></a>\n",
    "\n",
    "The remaining class methods are utility methods for generating the plots.  Many are focused on transforming between different coordinate systems:\n",
    "\n",
    "1. (a1, a2) : fractional coordinates along a1vect and a2vect.  \n",
    "2. pos : Cartesian position coordinates. \n",
    "3. (x, y) : plotting coordinates.\n",
    "\n",
    "Transforming from (a1, a2) to pos requires a1vect, a2vect, and optionally the box.  Transforming from pos to (x, y) requires specifying which Cartesian vector to align with the x-axis of the plot. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.1. E_gsf()\n",
    "\n",
    "Returns values for generalized stacking fault energy interpolated from the raw data.  Values can be obtained relative to a1, a2 fractional coordinates, x, y plotting coordinates, or pos Cartesian coordinates.\n",
    "        \n",
    "Parameters\n",
    "\n",
    "- **a1** (*float(s), optional*) Fractional coordinate(s) along a1vect.\n",
    "- **a2** (*float(s), optional*) Fractional coordinate(s) along a2vect.\n",
    "- **pos** (*np.array, optional*) 3D Cartesian position vector(s).\n",
    "- **x** (*float(s), optional*) Plotting x coordinate(s).\n",
    "- **y** (*float(s), optional*) Plotting y coordinate(s).\n",
    "- **a1vect** (*np.array, optional*) Vector for the a1 fractional coordinates.  Default value of None uses the saved a1vect.\n",
    "- **a2vect** (*np.array, optional*) Vector for the a2 fractional coordinates.  Default value of None uses the saved a2vect.\n",
    "- **xvect** (*np.array, optional*) Cartesian vector corresponding to the plotting x-axis. If None (default), this is taken as the Cartesian of a1vect.\n",
    "- **smooth** (*bool, optional*) If True (default) the returned values are smoothed using a RBF fit. If False, the closest measured values are returned.\n",
    "\n",
    "Returns \n",
    "\n",
    "- (*float or numpy.ndarray*) the energy values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Close to E_isf = 127.0843667373251 mJ/m^2\n",
      "Close to E_usf = 471.0258819751663 mJ/m^2\n"
     ]
    }
   ],
   "source": [
    "print(f'Close to E_isf = {uc.get_in_units(gamma.E_gsf(a1=1/3, a2=1/3), \"mJ/m^2\")} mJ/m^2')\n",
    "print(f'Close to E_usf = {uc.get_in_units(gamma.E_gsf(a1=2/3, a2=2/3), \"mJ/m^2\")} mJ/m^2')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.2 delta()\n",
    "\n",
    "Returns values for the relaxation distance interpolated from the raw data.  Values can be obtained relative to a1, a2 fractional coordinates, x, y plotting coordinates, or pos Cartesian coordinates.\n",
    "        \n",
    "Parameters\n",
    "\n",
    "- **a1** (*float(s), optional*) Fractional coordinate(s) along a1vect.\n",
    "- **a2** (*float(s), optional*) Fractional coordinate(s) along a2vect.\n",
    "- **pos** (*np.array, optional*) 3D Cartesian position vector(s).\n",
    "- **x** (*float(s), optional*) Plotting x coordinate(s).\n",
    "- **y** (*float(s), optional*) Plotting y coordinate(s).\n",
    "- **a1vect** (*np.array, optional*) Vector for the a1 fractional coordinates.  Default value of None uses the saved a1vect.\n",
    "- **a2vect** (*np.array, optional*) Vector for the a2 fractional coordinates.  Default value of None uses the saved a2vect.\n",
    "- **xvect** (*np.array, optional*) Cartesian vector corresponding to the plotting x-axis. If None (default), this is taken as the Cartesian of a1vect.\n",
    "- **smooth** (*bool, optional*) If True (default) the returned values are smoothed using a RBF fit. If False, the closest measured values are returned.\n",
    "\n",
    "Returns \n",
    "\n",
    "- (*float or numpy.ndarray*) the relaxation distance values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Close to δ_isf = 0.04908088528014787 angstrom\n",
      "Close to δ_usf = 0.3865334761953485 angstrom\n"
     ]
    }
   ],
   "source": [
    "print(f'Close to δ_isf = {uc.get_in_units(gamma.delta(a1=1/3, a2=1/3), \"angstrom\")} angstrom')\n",
    "print(f'Close to δ_usf = {uc.get_in_units(gamma.delta(a1=2/3, a2=2/3), \"angstrom\")} angstrom')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6.3 Conversion methods\n",
    "\n",
    "Parameters as defined above\n",
    "\n",
    "- **a12_to_pos(a1, a2, a1vect=None, a2vect=None)**\n",
    "- **pos_to_xy(pos, xvect=None)**\n",
    "- **a12_to_xy(a1, a2, a1vect=None, a2vect=None, xvect=None)**\n",
    "- **pos_to_a12(pos, a1vect=None, a2vect=None)**\n",
    "- **xy_to_pos(x, y, xvect=None)**\n",
    "- **xy_to_a12(x, y, a1vect=None, a2vect=None, xvect=None)**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__File cleanup__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "Path('gamma.json').unlink()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
